Semantics-guided reconstruction of indoor navigation elements from 3D colorized points

Yang, Juntao; Zhang, Kang; Zeng, Liping; Akwensi, Perpetual Hope; Sester, Monika

doi:10.1016/j.isprsjprs.2021.01.013

Cited by 28 publications

(11 citation statements)

References 50 publications

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“…Real 3D, DTs, smart cities and other concepts have radically altered the architecture industry. Yang et al, (2021) [73] stated that true 3D is built by transporting structural and semantic geographical entities that support human-machine compatible understanding and real-time perception of the IoT on 3D geographical scenes. The digital elevation model, digital surface model, digital orthophoto, real orthophoto, oblique 3D model and laser point cloud are all examples of geographic scenes.…”

Section: Intelligent Green Building In a Digital Twin Smart Citymentioning

confidence: 99%

Digital Twins for Intelligent Green Buildings

Yang

Wang

2022

Buildings

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At present, the integration of green building, the intelligent building industry and high-quality development are facing a series of new opportunities and challenges. This review aims to analyze the digital development of smart green buildings to make it easier to create contiguous ecological development areas in green ecological cities. It sorts out the main contents of Intelligent Green Buildings (IGB) and summarizes the application and role of Digital Twins (DTs) in intelligent buildings. Firstly, the basic connotations and development direction of IGB are deeply discussed, and the current realization and applications of IGB are analyzed. Then, the advantages of DTs are further investigated in the context of IGB for DT smart cities. Finally, the development trends and challenges of IGB are analyzed. After a review and research, it is found that the realization and application of IGB have been implemented, but the application of DTs remains not quite integrated into the design of IGB. Therefore, a forward-looking design is required when designing the IGBs, such as prioritizing sustainable development, people’s livelihoods and green structures. At the same time, an IGB can only show its significance after the basic process of building the application layer is performed correctly. Therefore, this review contributes to the proper integration of IGB and urban development strategies, which are crucial to encouraging the long-term development of cities, thus providing a theoretical basis and practical experience for promoting the development of smart cities.

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Section: Intelligent Green Building In a Digital Twin Smart Citymentioning

confidence: 99%

Digital Twins for Intelligent Green Buildings

Yang

Wang

2022

Buildings

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“…To obtain realistic 3D interior models, the Plan2Scene [44] proposed an efficient GCN architecture that inferred textures for unobserved surfaces based on residential floor-plans and a set of associated photos. To realize indoor localization services that require the indoor spatial information and the relationships between indoor spaces, [45] proposed a semantics-guided method for deducing topology of indoor spaces. In their developed hierarchical framework, a GCN-based method was used to model the longrange relationships among primitives in the real world.…”

Section: B Floor-plan Image Structuringmentioning

confidence: 99%

Automated Semantics and Topology Representation of Residential-Building Space Using Floor-Plan Raster Maps

Wang

Jiang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Automatically representing the semantics and topology of indoor building spaces from floor-plans is necessary for many applications, such as architectural design and indoor renovations. Extensive studies have investigated reconstructing indoor spaces with semantics and topology using professional means (e.g., laser scanning and photogrammetry). Floor-plan raster maps are widely and freely available for various purposes. Nevertheless, there is little research on the semantic and topological representation of indoor elements from floor-plan raster maps. To fill this gap, we propose a method of automatically representing the semantics and topology of indoor spaces from floor-plan raster maps. The proposed method first identifies basic geometric primitives from floor-plans using a learning-based hierarchical segmentation approach. Second, the relationship between the detected geometric primitives is assembled into the planar structure representation with topological data using mixed integer programming. Finally, the floor-plan graph structure is checked and optimized to maintain consistency with a polygonal coordinate descent strategy, resulting in a correct representation of the semantics and topology of the indoor space. Comprehensive evaluations demonstrate that the proposed method effectively achieves superior performance in three different datasets. The proposed method allows for 3D model popups for better visualizations and direct architectural model manipulations of the interior building layouts computation.

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“…In summary, although the reconstruction of indoor structures has been studied in the past few years, generating a topologically-consistent semantic model in a complex environment, such as uneven ceiling, non-orthogonal walls, or irregular shape, is still a challenge [32][33][34]. Most published methods are based on strong structural assumptions or pre-definitions, i.e., they are limited to regularly shaped indoor structures.…”

Section: Related Workmentioning

confidence: 99%

Topologically Consistent Reconstruction for Complex Indoor Structures from Point Clouds

Shan

2021

Remote Sensing

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Indoor structures are composed of ceilings, walls and floors that need to be modeled for a variety of applications. This paper proposes an approach to reconstructing models of indoor structures in complex environments. First, semantic pre-processing, including segmentation and occlusion construction, is applied to segment the input point clouds to generate semantic patches of structural primitives with uniform density. Then, a primitives extraction method with detected boundary is introduced to approximate both the mathematical surface and the boundary of the patches. Finally, a constraint-based model reconstruction is applied to achieve the final topologically consistent structural model. Under this framework, both the geometric and structural constraints are considered in a holistic manner to assure topologic regularity. Experiments were carried out with both synthetic and real-world datasets. The accuracy of the proposed method achieved an overall reconstruction quality of approximately 4.60 cm of root mean square error (RMSE) and 94.10% Intersection over Union (IoU) of the input point cloud. The development can be applied for structural reconstruction of various complex indoor environments.

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Semantics-guided reconstruction of indoor navigation elements from 3D colorized points

Cited by 28 publications

References 50 publications

Digital Twins for Intelligent Green Buildings

Digital Twins for Intelligent Green Buildings

Automated Semantics and Topology Representation of Residential-Building Space Using Floor-Plan Raster Maps

Topologically Consistent Reconstruction for Complex Indoor Structures from Point Clouds

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